HYBRID APPROACH FOR CLASSIFICATION OF MULTILABEL MEDICAL DATA USING CLASSIFICATION APPROACH

Medical data has been analyzed by medicos for better understanding of reports and information driven through various tests. There are chances to use machine learning to generate results based on certain criteria added with the help of human intelligence. The main aim of this research is to classify data for such further analysis. Exploratory data analysis (EDA) is performed for different set of data to focus on important features to get maximum insights from a data set. The use of analytics in healthcare improves care by facilitating preventive care and EDA is a vital step while analyzing data. In this paper, the important factors are studies and the missing factors are predicted using K-means algorithm. The research proposes to use EDA along with machine learning techniques for classification of results. The result will generate categories that identifies words of medical terminolog based on theirrelations.